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Breiman's work helped to bridge the gap between statistics and computer science, particularly in the field of machine learning.
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His primary specialty is theoretical and applied machine learning.
His work led to the development of the boosting meta-algorithm used in machine learning.
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In machine learning and statistics, classification is the problem of identifying which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
In this post, I won't go into the reasons why I think things have gotten so out of control; I have some ideas, but I'm also dumbfounded.